How to use Guardrails

Ragbits offers an expandable guardrails system. You can use one of the available guardrails or create your own to prevent toxic language, PII leaks etc.

In this guide we will show you how to use guardrail based on OpenAI moderation and how to creat your own guardrail.

Using existing guardrail

To use one of the existing guardrails you need to import it together with GuardrailManager. Next you simply pass a list of guardrails to the manager and call verify() function that will check the input (str or Prompt) against all provided guardrails asynchronously.

import asyncio
from ragbits.guardrails.base import GuardrailManager, GuardrailVerificationResult
from ragbits.guardrails.openai_moderation import OpenAIModerationGuardrail


async def verify_message(message: str) -> list[GuardrailVerificationResult]:
    manager = GuardrailManager([OpenAIModerationGuardrail()])
    return await manager.verify(message)


if __name__ == '__main__':
    print(asyncio.run(verify_message("Test message")))

The expected output is an object with the following properties:

    guardrail_name: str
    succeeded: bool
    fail_reason: str | None

It allows you to see which guardrail was used, whether the check was successful and optionally a fail reason.

Implementing custom guardrail

We need to create a new class that inherits from Guardrail and implements abstract method verify.

from ragbits.core.prompt import Prompt
from ragbits.guardrails.base import Guardrail, GuardrailVerificationResult

class CustomGuardrail(Guardrail):

    async def verify(self, input_to_verify: Prompt | str) -> GuardrailVerificationResult:
        pass

With that you can pass your CustomGuardrail to the GuardrailManager as shown in using existing guardrails section.